This file serves to be a supplementary document that describes all the statistics results performed for this project. It may help to test some new questions that are not included in the corresponding slides.
This file displays the results of the FaceWord project (data collected at NYU). There are two experiments in this project. In Experiment 1, Chinese participants viewed Chinese faces and characters in four conditions (Layout: intact, exchange [top and bottom parts were switched], top and bottom) and completed an additional localizer (Chinese faces, Chinese characters, objects, scrambled objects). In Experiment 2, English speakers viewed Chinese characters and English words in four conditions (Layout: intact, exchange, top [top parts of Chinese characters; left two letters for English words] and bottom [bottom parts of Chinese characters; right four letters for English words]) and completed an additional localizer (Caucasian faces, English words, objects, scrambled objects).
For the main runs, analysis is conducted for each ROI separately (FFA1, FFA2, VWFA, LOC).
For each ROI, three analyses are performed:
libsvm is used to decode different condition pairs (see below) and one-tail one-sample t-tests is used to test if the pair of conditions can be decoded [whether the accuracy is significantly larger than the chancel level (0.5); one-tail one-sample t-tests]. Leave-one(-run)-out cross-validation is applied. No normalized or demean were used.
The probability was estimated for each particiapnt separately:
libsvm) is trained with the patterns of intact vs. exchange (10 runs).The above table displays the size (in mm2) of each label for each participant. (NA denotes that this label is not available for that particiapnt.)
The above table displays the number of vertices for each label and each participant. (NA denotes that this label is not available for that particiapnt.)
The above table dispalys the number of participants included in the following analyses for each ROI. (VWFA is only found on the left hemisphere.)
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 11 0.27 1.76 .03 .21
## 2 Layout 2.01, 22.10 0.04 7.70 ** .04 .003
## 3 FaceWord:Layout 2.48, 27.23 0.02 3.43 * .01 .04
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
##
## Univariate Type III Repeated-Measures ANOVA Assuming Sphericity
##
## Sum Sq num Df Error SS den Df F value Pr(>F)
## (Intercept) 118.363 1 11.8360 11 110.0021 4.582e-07 ***
## FaceWord 0.478 1 2.9859 11 1.7616 0.2113156
## Layout 0.648 3 0.9258 33 7.7044 0.0004909 ***
## FaceWord:Layout 0.206 3 0.6612 33 3.4288 0.0281837 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Mauchly Tests for Sphericity
##
## Test statistic p-value
## Layout 0.46669 0.19414
## FaceWord:Layout 0.73618 0.70485
##
##
## Greenhouse-Geisser and Huynh-Feldt Corrections
## for Departure from Sphericity
##
## GG eps Pr(>F[GG])
## Layout 0.66969 0.002863 **
## FaceWord:Layout 0.82528 0.038221 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## HF eps Pr(>F[HF])
## Layout 0.8196706 0.001279953
## FaceWord:Layout 1.0835919 0.028183674
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## faces - words 0.141 0.106 11 1.327 0.2113
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.0655 0.0484 33 1.354 0.5365
## intact - top 0.2121 0.0484 33 4.387 0.0006
## intact - bottom 0.1601 0.0484 33 3.310 0.0116
## exchange - top 0.1467 0.0484 33 3.034 0.0231
## exchange - bottom 0.0946 0.0484 33 1.957 0.2250
## top - bottom -0.0521 0.0484 33 -1.077 0.7057
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . faces - words 0.2124 0.1175 16.1 1.807 0.0894
## exchange . faces - words 0.0580 0.1175 16.1 0.493 0.6286
## top . faces - words 0.2527 0.1175 16.1 2.150 0.0471
## bottom . faces - words 0.0416 0.1175 16.1 0.354 0.7281
## . faces intact - exchange 0.1427 0.0633 64.2 2.254 0.0276
## . faces intact - top 0.1920 0.0633 64.2 3.033 0.0035
## . faces intact - bottom 0.2455 0.0633 64.2 3.877 0.0003
## . faces exchange - top 0.0493 0.0633 64.2 0.779 0.4388
## . faces exchange - bottom 0.1028 0.0633 64.2 1.624 0.1093
## . faces top - bottom 0.0535 0.0633 64.2 0.845 0.4014
## . words intact - exchange -0.0118 0.0633 64.2 -0.186 0.8531
## . words intact - top 0.2323 0.0633 64.2 3.669 0.0005
## . words intact - bottom 0.0746 0.0633 64.2 1.179 0.2427
## . words exchange - top 0.2440 0.0633 64.2 3.855 0.0003
## . words exchange - bottom 0.0864 0.0633 64.2 1.365 0.1770
## . words top - bottom -0.1576 0.0633 64.2 -2.490 0.0154
2(face vs. word)$$2(intact vs. exchange) ANOVA
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 16 0.38 15.48 ** .13 .001
## 2 Layout 2.48, 39.61 0.05 4.78 ** .02 .009
## 3 FaceWord:Layout 2.40, 38.44 0.05 2.66 + .009 .07
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## faces - words 0.418 0.106 16 3.935 0.0012
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.151540 0.0515 48 2.942 0.0250
## intact - top 0.171197 0.0515 48 3.323 0.0090
## intact - bottom 0.151656 0.0515 48 2.944 0.0248
## exchange - top 0.019657 0.0515 48 0.382 0.9809
## exchange - bottom 0.000116 0.0515 48 0.002 1.0000
## top - bottom -0.019541 0.0515 48 -0.379 0.9812
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . faces - words 0.590236 0.123 27.5 4.802 <.0001
## exchange . faces - words 0.335061 0.123 27.5 2.726 0.0110
## top . faces - words 0.374888 0.123 27.5 3.050 0.0050
## bottom . faces - words 0.372958 0.123 27.5 3.034 0.0052
## . faces intact - exchange 0.279127 0.072 96.0 3.875 0.0002
## . faces intact - top 0.278870 0.072 96.0 3.871 0.0002
## . faces intact - bottom 0.260294 0.072 96.0 3.613 0.0005
## . faces exchange - top -0.000257 0.072 96.0 -0.004 0.9972
## . faces exchange - bottom -0.018833 0.072 96.0 -0.261 0.7943
## . faces top - bottom -0.018576 0.072 96.0 -0.258 0.7971
## . words intact - exchange 0.023952 0.072 96.0 0.332 0.7403
## . words intact - top 0.063523 0.072 96.0 0.882 0.3801
## . words intact - bottom 0.043017 0.072 96.0 0.597 0.5518
## . words exchange - top 0.039571 0.072 96.0 0.549 0.5841
## . words exchange - bottom 0.019065 0.072 96.0 0.265 0.7919
## . words top - bottom -0.020506 0.072 96.0 -0.285 0.7765
## FaceWord_pairwise Layout_pairwise estimate SE df t.ratio p.value
## faces - words intact - exchange 0.255 0.111 16 2.300 0.0353
The above figure shows the neural respones (beta values) in FFA1 for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the decoding accuracy in FFA1 for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the probability of top+bottom being decoded as exchange conditions in FFA1. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 11 0.07 2.65 .01 .13
## 2 Layout 2.39, 26.30 0.02 6.90 ** .02 .003
## 3 FaceWord:Layout 2.31, 25.37 0.04 0.21 .001 .84
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## faces - words 0.0908 0.0558 11 1.628 0.1318
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.1022 0.0404 33 2.531 0.0734
## intact - top 0.1830 0.0404 33 4.532 0.0004
## intact - bottom 0.0863 0.0404 33 2.138 0.1624
## exchange - top 0.0808 0.0404 33 2.001 0.2082
## exchange - bottom -0.0159 0.0404 33 -0.394 0.9790
## top - bottom -0.0967 0.0404 33 -2.394 0.0980
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . faces - words 0.13378 0.0822 35.6 1.627 0.1126
## exchange . faces - words 0.07368 0.0822 35.6 0.896 0.3762
## top . faces - words 0.06034 0.0822 35.6 0.734 0.4678
## bottom . faces - words 0.09558 0.0822 35.6 1.162 0.2528
## . faces intact - exchange 0.13228 0.0637 63.5 2.075 0.0420
## . faces intact - top 0.21976 0.0637 63.5 3.448 0.0010
## . faces intact - bottom 0.10544 0.0637 63.5 1.654 0.1030
## . faces exchange - top 0.08748 0.0637 63.5 1.373 0.1747
## . faces exchange - bottom -0.02684 0.0637 63.5 -0.421 0.6751
## . faces top - bottom -0.11433 0.0637 63.5 -1.794 0.0776
## . words intact - exchange 0.07219 0.0637 63.5 1.133 0.2617
## . words intact - top 0.14633 0.0637 63.5 2.296 0.0250
## . words intact - bottom 0.06724 0.0637 63.5 1.055 0.2954
## . words exchange - top 0.07414 0.0637 63.5 1.163 0.2491
## . words exchange - bottom -0.00494 0.0637 63.5 -0.078 0.9384
## . words top - bottom -0.07909 0.0637 63.5 -1.241 0.2193
2(face vs. word)$$2(intact vs. exchange) ANOVA
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 12 0.20 9.78 ** .10 .009
## 2 Layout 2.55, 30.55 0.03 8.80 *** .03 .0004
## 3 FaceWord:Layout 2.42, 29.00 0.03 3.41 * .01 .04
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## faces - words 0.277 0.0885 12 3.128 0.0087
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.18454 0.0413 36 4.472 0.0004
## intact - top 0.17936 0.0413 36 4.346 0.0006
## intact - bottom 0.14400 0.0413 36 3.489 0.0068
## exchange - top -0.00517 0.0413 36 -0.125 0.9993
## exchange - bottom -0.04054 0.0413 36 -0.982 0.7603
## top - bottom -0.03537 0.0413 36 -0.857 0.8267
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . faces - words 0.44174 0.1040 21.8 4.249 0.0003
## exchange . faces - words 0.16857 0.1040 21.8 1.622 0.1193
## top . faces - words 0.25457 0.1040 21.8 2.449 0.0228
## bottom . faces - words 0.24210 0.1040 21.8 2.329 0.0295
## . faces intact - exchange 0.32112 0.0607 71.6 5.288 <.0001
## . faces intact - top 0.27295 0.0607 71.6 4.494 <.0001
## . faces intact - bottom 0.24382 0.0607 71.6 4.015 0.0001
## . faces exchange - top -0.04817 0.0607 71.6 -0.793 0.4303
## . faces exchange - bottom -0.07730 0.0607 71.6 -1.273 0.2072
## . faces top - bottom -0.02913 0.0607 71.6 -0.480 0.6329
## . words intact - exchange 0.04795 0.0607 71.6 0.790 0.4324
## . words intact - top 0.08578 0.0607 71.6 1.412 0.1622
## . words intact - bottom 0.04417 0.0607 71.6 0.727 0.4694
## . words exchange - top 0.03782 0.0607 71.6 0.623 0.5354
## . words exchange - bottom -0.00378 0.0607 71.6 -0.062 0.9506
## . words top - bottom -0.04160 0.0607 71.6 -0.685 0.4956
2(face vs. word)$$2(intact vs. exchange) ANOVA
The above figure shows the neural respones (beta values) in FFA2 for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the decoding accuracy in FFA2 for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the probability of top+bottom being decoded as exchange conditions in FFA2. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 17 0.21 100.25 *** .25 <.0001
## 2 Layout 2.53, 43.04 0.03 4.04 * .005 .02
## 3 FaceWord:Layout 2.57, 43.65 0.03 5.40 ** .005 .005
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## faces - words -0.773 0.0772 17 -10.012 <.0001
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange -0.05205 0.0368 51 -1.413 0.4974
## intact - top 0.07544 0.0368 51 2.048 0.1844
## intact - bottom 0.00925 0.0368 51 0.251 0.9944
## exchange - top 0.12748 0.0368 51 3.460 0.0059
## exchange - bottom 0.06130 0.0368 51 1.664 0.3531
## top - bottom -0.06619 0.0368 51 -1.796 0.2868
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . faces - words -0.69862 0.0881 27.9 -7.932 <.0001
## exchange . faces - words -0.90436 0.0881 27.9 -10.268 <.0001
## top . faces - words -0.65964 0.0881 27.9 -7.490 <.0001
## bottom . faces - words -0.82940 0.0881 27.9 -9.417 <.0001
## . faces intact - exchange 0.05082 0.0505 101.6 1.005 0.3171
## . faces intact - top 0.05595 0.0505 101.6 1.107 0.2710
## . faces intact - bottom 0.07464 0.0505 101.6 1.477 0.1429
## . faces exchange - top 0.00513 0.0505 101.6 0.101 0.9194
## . faces exchange - bottom 0.02382 0.0505 101.6 0.471 0.6385
## . faces top - bottom 0.01869 0.0505 101.6 0.370 0.7123
## . words intact - exchange -0.15491 0.0505 101.6 -3.065 0.0028
## . words intact - top 0.09493 0.0505 101.6 1.878 0.0633
## . words intact - bottom -0.05614 0.0505 101.6 -1.111 0.2694
## . words exchange - top 0.24984 0.0505 101.6 4.943 <.0001
## . words exchange - bottom 0.09878 0.0505 101.6 1.954 0.0534
## . words top - bottom -0.15106 0.0505 101.6 -2.989 0.0035
2(face vs. word)$$2(intact vs. exchange) ANOVA
The above figure shows the neural respones (beta values) in VWFA for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: *, p < .05
The above figure shows the decoding accuracy in VWFA for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: ***, p <.001
The above figure shows the probability of top+bottom being decoded as exchange conditions in VWFA. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 18 0.25 20.47 *** .06 .0003
## 2 Layout 2.40, 43.14 0.05 4.27 * .006 .02
## 3 FaceWord:Layout 2.40, 43.22 0.03 0.33 .0003 .76
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## faces - words -0.366 0.081 18 -4.524 0.0003
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.00111 0.0439 54 0.025 1.0000
## intact - top 0.13678 0.0439 54 3.113 0.0152
## intact - bottom 0.04640 0.0439 54 1.056 0.7174
## exchange - top 0.13567 0.0439 54 3.088 0.0163
## exchange - bottom 0.04529 0.0439 54 1.031 0.7323
## top - bottom -0.09038 0.0439 54 -2.057 0.1805
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . faces - words -0.33462 0.0927 30 -3.610 0.0011
## exchange . faces - words -0.35596 0.0927 30 -3.841 0.0006
## top . faces - words -0.36872 0.0927 30 -3.978 0.0004
## bottom . faces - words -0.40576 0.0927 30 -4.378 0.0001
## . faces intact - exchange 0.01178 0.0573 105 0.205 0.8377
## . faces intact - top 0.15383 0.0573 105 2.682 0.0085
## . faces intact - bottom 0.08197 0.0573 105 1.429 0.1559
## . faces exchange - top 0.14205 0.0573 105 2.477 0.0148
## . faces exchange - bottom 0.07019 0.0573 105 1.224 0.2237
## . faces top - bottom -0.07186 0.0573 105 -1.253 0.2130
## . words intact - exchange -0.00955 0.0573 105 -0.167 0.8680
## . words intact - top 0.11974 0.0573 105 2.088 0.0392
## . words intact - bottom 0.01083 0.0573 105 0.189 0.8505
## . words exchange - top 0.12929 0.0573 105 2.254 0.0262
## . words exchange - bottom 0.02039 0.0573 105 0.356 0.7229
## . words top - bottom -0.10890 0.0573 105 -1.899 0.0603
2(face vs. word)$$2(intact vs. exchange) ANOVA
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 17 0.20 8.43 ** .02 .010
## 2 Layout 2.18, 37.07 0.07 1.47 .002 .24
## 3 FaceWord:Layout 2.63, 44.74 0.03 1.27 .001 .30
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## faces - words -0.217 0.0747 17 -2.904 0.0099
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.0825 0.0532 51 1.551 0.4156
## intact - top 0.1037 0.0532 51 1.948 0.2212
## intact - bottom 0.0449 0.0532 51 0.843 0.8339
## exchange - top 0.0212 0.0532 51 0.398 0.9785
## exchange - bottom -0.0377 0.0532 51 -0.708 0.8935
## top - bottom -0.0589 0.0532 51 -1.106 0.6877
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . faces - words -0.14282 0.0893 32.6 -1.600 0.1193
## exchange . faces - words -0.29775 0.0893 32.6 -3.335 0.0021
## top . faces - words -0.21835 0.0893 32.6 -2.446 0.0200
## bottom . faces - words -0.20910 0.0893 32.6 -2.342 0.0254
## . faces intact - exchange 0.16001 0.0665 94.5 2.406 0.0181
## . faces intact - top 0.14149 0.0665 94.5 2.127 0.0360
## . faces intact - bottom 0.07800 0.0665 94.5 1.173 0.2439
## . faces exchange - top -0.01853 0.0665 94.5 -0.279 0.7812
## . faces exchange - bottom -0.08202 0.0665 94.5 -1.233 0.2206
## . faces top - bottom -0.06349 0.0665 94.5 -0.954 0.3423
## . words intact - exchange 0.00508 0.0665 94.5 0.076 0.9393
## . words intact - top 0.06595 0.0665 94.5 0.992 0.3240
## . words intact - bottom 0.01171 0.0665 94.5 0.176 0.8606
## . words exchange - top 0.06087 0.0665 94.5 0.915 0.3625
## . words exchange - bottom 0.00663 0.0665 94.5 0.100 0.9208
## . words top - bottom -0.05424 0.0665 94.5 -0.815 0.4169
2(face vs. word)$$2(intact vs. exchange) ANOVA
The above figure shows the neural respones (beta values) in LO for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: *, p < .05
The above figure shows the decoding accuracy in LO for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: , p < .01; *, p <.001
The above figure shows the probability of top+bottom being decoded as exchange conditions in LO. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
The above table displays the size (in mm2) of each label for each participant. (NA denotes that this label is not available for that particiapnt.)
The above table displays the number of vertices for each label and each participant. (NA denotes that this label is not available for that particiapnt.)
The above table dispalys the number of participants included in the following analyses for each ROI. (VWFA is only found on the left hemisphere.)
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 11 0.22 12.53 ** .10 .005
## 2 Layout 1.73, 19.00 0.03 3.34 + .007 .06
## 3 FaceWord:Layout 2.25, 24.78 0.04 4.10 * .01 .03
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## English - Chinese 0.338 0.0954 11 3.539 0.0046
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange -0.10656 0.0394 33 -2.706 0.0499
## intact - partA 0.00125 0.0394 33 0.032 1.0000
## intact - partB -0.04698 0.0394 33 -1.193 0.6354
## exchange - partA 0.10781 0.0394 33 2.738 0.0464
## exchange - partB 0.05958 0.0394 33 1.513 0.4414
## partA - partB -0.04823 0.0394 33 -1.225 0.6159
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . English - Chinese 0.34336 0.1134 20.8 3.027 0.0065
## exchange . English - Chinese 0.44662 0.1134 20.8 3.937 0.0008
## partA . English - Chinese 0.13346 0.1134 20.8 1.176 0.2527
## partB . English - Chinese 0.42759 0.1134 20.8 3.769 0.0011
## . English intact - exchange -0.15819 0.0637 62.5 -2.483 0.0157
## . English intact - partA 0.10620 0.0637 62.5 1.667 0.1005
## . English intact - partB -0.08909 0.0637 62.5 -1.398 0.1669
## . English exchange - partA 0.26440 0.0637 62.5 4.150 0.0001
## . English exchange - partB 0.06910 0.0637 62.5 1.085 0.2823
## . English partA - partB -0.19530 0.0637 62.5 -3.065 0.0032
## . Chinese intact - exchange -0.05493 0.0637 62.5 -0.862 0.3919
## . Chinese intact - partA -0.10370 0.0637 62.5 -1.628 0.1086
## . Chinese intact - partB -0.00486 0.0637 62.5 -0.076 0.9394
## . Chinese exchange - partA -0.04877 0.0637 62.5 -0.765 0.4469
## . Chinese exchange - partB 0.05007 0.0637 62.5 0.786 0.4349
## . Chinese partA - partB 0.09884 0.0637 62.5 1.551 0.1259
2(face vs. word)$$2(intact vs. exchange) ANOVA
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 14 0.13 0.65 .008 .43
## 2 Layout 2.74, 38.34 0.03 2.08 .02 .12
## 3 FaceWord:Layout 2.18, 30.55 0.03 1.39 .009 .26
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## English - Chinese -0.0522 0.0648 14 -0.805 0.4341
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.0605 0.0406 42 1.490 0.4522
## intact - partA -0.0299 0.0406 42 -0.738 0.8814
## intact - partB 0.0445 0.0406 42 1.098 0.6929
## exchange - partA -0.0904 0.0406 42 -2.228 0.1323
## exchange - partB -0.0159 0.0406 42 -0.393 0.9792
## partA - partB 0.0745 0.0406 42 1.835 0.2716
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . English - Chinese 0.00632 0.0794 29.1 0.080 0.9371
## exchange . English - Chinese -0.13621 0.0794 29.1 -1.716 0.0969
## partA . English - Chinese -0.06054 0.0794 29.1 -0.763 0.4519
## partB . English - Chinese -0.01847 0.0794 29.1 -0.233 0.8177
## . English intact - exchange 0.13175 0.0552 83.5 2.387 0.0192
## . English intact - partA 0.00350 0.0552 83.5 0.063 0.9496
## . English intact - partB 0.05694 0.0552 83.5 1.032 0.3052
## . English exchange - partA -0.12825 0.0552 83.5 -2.324 0.0226
## . English exchange - partB -0.07481 0.0552 83.5 -1.355 0.1789
## . English partA - partB 0.05344 0.0552 83.5 0.968 0.3357
## . Chinese intact - exchange -0.01078 0.0552 83.5 -0.195 0.8456
## . Chinese intact - partA -0.06337 0.0552 83.5 -1.148 0.2542
## . Chinese intact - partB 0.03215 0.0552 83.5 0.582 0.5618
## . Chinese exchange - partA -0.05258 0.0552 83.5 -0.953 0.3434
## . Chinese exchange - partB 0.04293 0.0552 83.5 0.778 0.4389
## . Chinese partA - partB 0.09551 0.0552 83.5 1.731 0.0872
2(face vs. word)$$2(intact vs. exchange) ANOVA
The above figure shows the neural respones (beta values) in FFA1 for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the decoding accuracy in FFA1 for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the probability of top+bottom being decoded as exchange conditions in FFA1. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 12 0.18 8.65 * .08 .01
## 2 Layout 2.52, 30.24 0.02 0.84 .002 .47
## 3 FaceWord:Layout 2.56, 30.70 0.03 2.83 + .01 .06
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## English - Chinese 0.247 0.084 12 2.940 0.0124
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.01909 0.0343 36 0.556 0.9442
## intact - partA 0.02635 0.0343 36 0.768 0.8683
## intact - partB -0.02327 0.0343 36 -0.678 0.9047
## exchange - partA 0.00726 0.0343 36 0.212 0.9966
## exchange - partB -0.04236 0.0343 36 -1.234 0.6095
## partA - partB -0.04962 0.0343 36 -1.446 0.4799
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . English - Chinese 0.3426 0.1002 23.0 3.418 0.0024
## exchange . English - Chinese 0.2466 0.1002 23.0 2.460 0.0218
## partA . English - Chinese 0.0986 0.1002 23.0 0.984 0.3355
## partB . English - Chinese 0.2999 0.1002 23.0 2.992 0.0065
## . English intact - exchange 0.0671 0.0564 67.5 1.191 0.2379
## . English intact - partA 0.1484 0.0564 67.5 2.633 0.0105
## . English intact - partB -0.0019 0.0564 67.5 -0.034 0.9732
## . English exchange - partA 0.0813 0.0564 67.5 1.442 0.1539
## . English exchange - partB -0.0690 0.0564 67.5 -1.224 0.2250
## . English partA - partB -0.1503 0.0564 67.5 -2.666 0.0096
## . Chinese intact - exchange -0.0289 0.0564 67.5 -0.513 0.6096
## . Chinese intact - partA -0.0957 0.0564 67.5 -1.697 0.0942
## . Chinese intact - partB -0.0446 0.0564 67.5 -0.792 0.4311
## . Chinese exchange - partA -0.0667 0.0564 67.5 -1.184 0.2404
## . Chinese exchange - partB -0.0157 0.0564 67.5 -0.279 0.7811
## . Chinese partA - partB 0.0510 0.0564 67.5 0.905 0.3685
2(face vs. word)$$2(intact vs. exchange) ANOVA
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 17 0.04 0.01 <.0001 .94
## 2 Layout 2.52, 42.90 0.01 0.17 .0007 .89
## 3 FaceWord:Layout 2.26, 38.48 0.02 0.74 .006 .50
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## English - Chinese 0.00267 0.0349 17 0.077 0.9399
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.01481 0.0228 51 0.649 0.9154
## intact - partA 0.00129 0.0228 51 0.056 0.9999
## intact - partB 0.00568 0.0228 51 0.249 0.9945
## exchange - partA -0.01352 0.0228 51 -0.593 0.9338
## exchange - partB -0.00913 0.0228 51 -0.400 0.9781
## partA - partB 0.00440 0.0228 51 0.193 0.9974
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . English - Chinese 0.04391 0.0526 57 0.835 0.4073
## exchange . English - Chinese 0.00180 0.0526 57 0.034 0.9728
## partA . English - Chinese -0.04967 0.0526 57 -0.944 0.3489
## partB . English - Chinese 0.01464 0.0526 57 0.278 0.7817
## . English intact - exchange 0.03587 0.0394 92 0.910 0.3651
## . English intact - partA 0.04808 0.0394 92 1.220 0.2256
## . English intact - partB 0.02032 0.0394 92 0.516 0.6074
## . English exchange - partA 0.01221 0.0394 92 0.310 0.7574
## . English exchange - partB -0.01555 0.0394 92 -0.395 0.6941
## . English partA - partB -0.02776 0.0394 92 -0.704 0.4830
## . Chinese intact - exchange -0.00624 0.0394 92 -0.158 0.8744
## . Chinese intact - partA -0.04550 0.0394 92 -1.155 0.2512
## . Chinese intact - partB -0.00895 0.0394 92 -0.227 0.8208
## . Chinese exchange - partA -0.03926 0.0394 92 -0.996 0.3218
## . Chinese exchange - partB -0.00271 0.0394 92 -0.069 0.9454
## . Chinese partA - partB 0.03655 0.0394 92 0.927 0.3561
2(face vs. word)$$2(intact vs. exchange) ANOVA
The above figure shows the neural respones (beta values) in FFA2 for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the decoding accuracy in FFA2 for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: “*p<0.1;**p<0.05;***p<0.01”
The above figure shows the probability of top+bottom being decoded as exchange conditions in FFA2. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 13 0.26 66.19 *** .35 <.0001
## 2 Layout 2.25, 29.19 0.03 10.51 *** .02 .0002
## 3 FaceWord:Layout 1.62, 21.06 0.06 9.23 ** .03 .002
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## English - Chinese 0.786 0.0966 13 8.135 <.0001
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange -0.1739 0.0366 39 -4.748 0.0002
## intact - partA -0.0150 0.0366 39 -0.411 0.9763
## intact - partB -0.1217 0.0366 39 -3.323 0.0101
## exchange - partA 0.1588 0.0366 39 4.337 0.0006
## exchange - partB 0.0522 0.0366 39 1.425 0.4917
## partA - partB -0.1066 0.0366 39 -2.912 0.0289
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . English - Chinese 0.7486 0.1124 22.9 6.662 <.0001
## exchange . English - Chinese 0.9659 0.1124 22.9 8.596 <.0001
## partA . English - Chinese 0.5173 0.1124 22.9 4.604 0.0001
## partB . English - Chinese 0.9114 0.1124 22.9 8.111 <.0001
## . English intact - exchange -0.2825 0.0595 73.7 -4.749 <.0001
## . English intact - partA 0.1006 0.0595 73.7 1.692 0.0950
## . English intact - partB -0.2031 0.0595 73.7 -3.414 0.0010
## . English exchange - partA 0.3831 0.0595 73.7 6.441 <.0001
## . English exchange - partB 0.0794 0.0595 73.7 1.335 0.1859
## . English partA - partB -0.3037 0.0595 73.7 -5.106 <.0001
## . Chinese intact - exchange -0.0652 0.0595 73.7 -1.096 0.2766
## . Chinese intact - partA -0.1307 0.0595 73.7 -2.197 0.0312
## . Chinese intact - partB -0.0403 0.0595 73.7 -0.677 0.5006
## . Chinese exchange - partA -0.0655 0.0595 73.7 -1.101 0.2746
## . Chinese exchange - partB 0.0249 0.0595 73.7 0.419 0.6762
## . Chinese partA - partB 0.0904 0.0595 73.7 1.520 0.1328
2(face vs. word)$$2(intact vs. exchange) ANOVA
The above figure shows the neural respones (beta values) in VWFA for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: *, p < .05
The above figure shows the decoding accuracy in VWFA for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: ***, p <.001
The above figure shows the probability of top+bottom being decoded as exchange conditions in VWFA. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 15 0.19 4.47 + .01 .05
## 2 Layout 1.75, 26.29 0.05 1.37 .002 .27
## 3 FaceWord:Layout 2.06, 30.86 0.07 1.76 .004 .19
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## English - Chinese -0.161 0.0763 15 -2.115 0.0516
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange -0.05443 0.0416 45 -1.310 0.5617
## intact - partA -0.08268 0.0416 45 -1.989 0.2072
## intact - partB -0.04861 0.0416 45 -1.170 0.6489
## exchange - partA -0.02825 0.0416 45 -0.680 0.9043
## exchange - partB 0.00582 0.0416 45 0.140 0.9990
## partA - partB 0.03407 0.0416 45 0.820 0.8448
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . English - Chinese -0.1029 0.1002 38.0 -1.027 0.3109
## exchange . English - Chinese -0.0778 0.1002 38.0 -0.776 0.4426
## partA . English - Chinese -0.3003 0.1002 38.0 -2.996 0.0048
## partB . English - Chinese -0.1644 0.1002 38.0 -1.640 0.1092
## . English intact - exchange -0.0670 0.0674 85.1 -0.994 0.3230
## . English intact - partA 0.0160 0.0674 85.1 0.237 0.8131
## . English intact - partB -0.0179 0.0674 85.1 -0.265 0.7917
## . English exchange - partA 0.0830 0.0674 85.1 1.231 0.2216
## . English exchange - partB 0.0492 0.0674 85.1 0.729 0.4679
## . English partA - partB -0.0338 0.0674 85.1 -0.502 0.6169
## . Chinese intact - exchange -0.0418 0.0674 85.1 -0.621 0.5364
## . Chinese intact - partA -0.1813 0.0674 85.1 -2.690 0.0086
## . Chinese intact - partB -0.0794 0.0674 85.1 -1.177 0.2424
## . Chinese exchange - partA -0.1395 0.0674 85.1 -2.069 0.0415
## . Chinese exchange - partB -0.0375 0.0674 85.1 -0.556 0.5794
## . Chinese partA - partB 0.1020 0.0674 85.1 1.513 0.1340
2(face vs. word)$$2(intact vs. exchange) ANOVA
## Anova Table (Type 3 tests)
##
## Response: Response
## Effect df MSE F ges p.value
## 1 FaceWord 1, 16 0.14 45.30 *** .03 <.0001
## 2 Layout 2.29, 36.59 0.07 3.07 + .002 .05
## 3 FaceWord:Layout 2.16, 34.56 0.04 1.01 .0004 .38
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
##
## Sphericity correction method: GG
Posthoc analysis for the main effects:
## contrast estimate SE df t.ratio p.value
## English - Chinese -0.439 0.0652 16 -6.730 <.0001
##
## Results are averaged over the levels of: Layout
## contrast estimate SE df t.ratio p.value
## intact - exchange 0.08519 0.057 48 1.494 0.4490
## intact - partA -0.08754 0.057 48 -1.535 0.4250
## intact - partB -0.00879 0.057 48 -0.154 0.9987
## exchange - partA -0.17273 0.057 48 -3.029 0.0199
## exchange - partB -0.09398 0.057 48 -1.648 0.3621
## partA - partB 0.07875 0.057 48 1.381 0.5172
##
## Results are averaged over the levels of: FaceWord
## P value adjustment: tukey method for comparing a family of 4 estimates
Results of simple effect analysis (uncorrected):
## Layout FaceWord contrast estimate SE df t.ratio p.value
## intact . English - Chinese -0.3872 0.0835 37.9 -4.638 <.0001
## exchange . English - Chinese -0.5199 0.0835 37.9 -6.227 <.0001
## partA . English - Chinese -0.3982 0.0835 37.9 -4.770 <.0001
## partB . English - Chinese -0.4497 0.0835 37.9 -5.387 <.0001
## . English intact - exchange 0.1515 0.0712 88.8 2.129 0.0360
## . English intact - partA -0.0820 0.0712 88.8 -1.153 0.2522
## . English intact - partB 0.0225 0.0712 88.8 0.316 0.7529
## . English exchange - partA -0.2336 0.0712 88.8 -3.282 0.0015
## . English exchange - partB -0.1291 0.0712 88.8 -1.813 0.0731
## . English partA - partB 0.1045 0.0712 88.8 1.468 0.1455
## . Chinese intact - exchange 0.0188 0.0712 88.8 0.265 0.7918
## . Chinese intact - partA -0.0931 0.0712 88.8 -1.308 0.1944
## . Chinese intact - partB -0.0401 0.0712 88.8 -0.563 0.5750
## . Chinese exchange - partA -0.1119 0.0712 88.8 -1.572 0.1194
## . Chinese exchange - partB -0.0589 0.0712 88.8 -0.828 0.4101
## . Chinese partA - partB 0.0530 0.0712 88.8 0.745 0.4584
2(face vs. word)$$2(intact vs. exchange) ANOVA
The above figure shows the neural respones (beta values) in LO for each condition. The numbers are the p-values for the tests of differences between intact vs. exchange in that condition. Error bars represent 95% confidence intervals. Note: *, p < .05
The above figure shows the decoding accuracy in LO for each pair. The numbers are the p-values for the one-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals. Note: , p < .01; *, p <.001
The above figure shows the probability of top+bottom being decoded as exchange conditions in LO. Patterns of top and bottom were combined with different weights, i.e., “face_top0.25-face_bottom0.75” denotes the linear combinations of face_top and face_bottom with the weights of 0.25/0.75. The numbers are the p-values for the two-tail one-sample t-tests against the chance level (0.5) in that condition. Error bars represent 95% confidence intervals.
## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.5
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] tools stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggpubr_0.2.5 magrittr_2.0.1 emmeans_1.4.7 lmerTest_3.1-0 afex_0.25-1 lme4_1.1-21 Matrix_1.2-18 forcats_0.4.0 stringr_1.4.0 dplyr_0.8.5 purrr_0.3.3 readr_1.3.1 tidyr_1.0.2 tibble_3.0.1 ggplot2_3.3.0 tidyverse_1.2.1
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.1 jsonlite_1.7.1 splines_3.6.3 carData_3.0-3 modelr_0.1.5 assertthat_0.2.1 cellranger_1.1.0 yaml_2.2.1 numDeriv_2016.8-1.1 pillar_1.4.4 backports_1.1.5 lattice_0.20-38 glue_1.4.2 digest_0.6.27 ggsignif_0.6.0 rvest_0.3.5 minqa_1.2.4 colorspace_1.4-1 cowplot_1.0.0 htmltools_0.5.0 plyr_1.8.6 pkgconfig_2.0.3
## [23] broom_0.5.3.9000 haven_2.2.0 xtable_1.8-4 mvtnorm_1.0-11 scales_1.0.0 openxlsx_4.1.3 rio_0.5.16 generics_0.0.2 car_3.0-5 ellipsis_0.3.1 withr_2.1.2 cli_2.0.2 crayon_1.3.4 readxl_1.3.1 estimability_1.3 evaluate_0.14 fansi_0.4.1 nlme_3.1-144 MASS_7.3-51.5 xml2_1.2.2 foreign_0.8-75 data.table_1.12.6
## [45] hms_0.5.3 lifecycle_0.2.0 munsell_0.5.0 zip_2.0.4 compiler_3.6.3 rlang_0.4.8 grid_3.6.3 nloptr_1.2.1 rstudioapi_0.11 labeling_0.3 rmarkdown_2.1 boot_1.3-24 gtable_0.3.0 abind_1.4-5 curl_4.3 reshape2_1.4.3 R6_2.4.1 lubridate_1.7.4 knitr_1.30 stringi_1.5.3 parallel_3.6.3 Rcpp_1.0.4.6
## [67] vctrs_0.3.1 tidyselect_1.0.0 xfun_0.19 coda_0.19-3
A work by Haiyang Jin